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Developing and Evaluating a Mixed Sensor Smart Chair System for Real-time Posture Classification: Combining Pressure and Distance sensors by Jeong, Haeseok; Park, Woojin is a Computer Science article available to read on EtoBox.

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A novel sensor-embedded smart chair system was developed to monitor and classify a worker's sitting postures in real time. The smart chair system was a mixed sensor system utilizing six pressure sensors and six infrared reflective distance sensors in combination. The pressure sensors were embedded in the seat cushion to gather seat cushion pressure distribution data. The distance sensors were placed in the seatback to measure seatback-trunk distances at different locations in the frontal plane. The use of the seatback distance sensors represented a unique design feature, which distinguished the mixed sensor system from the previous posture monitoring systems. Employing a k-Nearest Neighbor algorithm, the mixed sensor system classified an instantaneous posture as one of posture categories determined based on an analysis of the ergonomics literature on sitting postures and sitting-related musculoskeletal problems. The mixed sensor system was evaluated in posture classification performance in comparison with two benchmark systems that utilized only a single type of sensors. The purpose of the comparisons was to determine the utility of the design combining seat cushion pressure sensor

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Author

Jeong, Haeseok; Park, Woojin

Publisher

Institute of Electrical and Electronics Engineers; Institute of Electrical and Electronics Engineers Inc.; Institute of Electrical and Electronics Engineers (IEEE) (ISSN 2168-2194)

Published

2021

Language

EN

Field

Computer Science (Physical Sciences)